数据集的识别，可以用作实验的分类…

1、编制程序显示印章图像（24位真彩色位图）； 2、读出位图中每一像素点的（R，G，B）样本值； 3、以RGB其中某两个（或三个）为坐标，取一定数量的图像点为分析样本，分析其坐标系中的分布； 4、采用本章学习的方法找到分类判别函数，对这些样本进行分类；（要求首先将印章与底纹区分，如有可能将印章、底纹、签字区分） 5、将分类后的结果标记到原始图像上，检查其效果。 -1, the preparation procedures showed that the seal image (24-bit true color bitmap) 2, read out each bitmap pixel (R, G, B) sample value 3 to RGB which a two (or three ) for the coordinates, take a certain number of image points for the analysis of samples, analysis of its coordinate system of distribution 4, the method used in this chapter to learn to find discriminant function classification of these samples for classification (required first to distinguish between the seal and Shading, if possible, will seal, Shading, signatures to distinguish between) 5, will be the result of classification markings to the original image to check its effectiveness.

详细介绍了有关人工智能软件编写的理论和实务-details of the artificial intelligence software prepared by the theory and practice

遗传算法学习资料-GA learning materials

打开压缩包，其中的word文档中提供了“m个工件分配给m架机床的效益最优化问题，使用一种遗传算法解决。”的整个编程思路和过程分析。望有相关需要的朋友喜欢-open compressed, the word document provided "m m allocated to the workpiece-machine efficiency optimization, the use of a genetic algorithm to solve." The entire programming ideas and process analysis. Expect relevant to the needs of friends like

利用c语言实现人工智能神经网络的bam算法-Using c language bam neural network artificial intelligence algorithms

模糊技术与神经网络技术选编-fuzzy and neural network technology Selected

Neural Networks ，8种神经网络，BP，RBF，CPN等通过VC++来实现了！-Neural Networks, 8 Neuro network, BP, RBF, CPN, such as through VC++ To achieve!

随机神经网络工具箱-random neural network toolbox

中科院张的摄像机内外参数标定的源码和例子，可以在计算机视觉计算中试用-Chinese Academy of Sciences and outside the parameters of the camera calibration of the source code and examples, the computer can calculate the visual trial

分布估计算法（EDA）讲义，29页PPT 1. 从GA到 EDA 2. 链接学习与模型 3. 连续EDA 4. EDA 与玻耳兹曼分布 5. 资源 -estimation of distribution algorithm（EDA）tutorial 1. from the GA to the EDA 2. Linking learning and models 3. Continuous EDA 4. EDA with Boltzmann distribution 5. other Resources